Finding news curators in twitter

Users interact with online news in many ways, one of them being sharing content through online social networking sites such as Twitter. There is a small but important group of users that devote a substantial amount of effort and care to this activity. These users monitor a large variety of sources on a topic or around a story, carefully select interesting material on this topic, and disseminate it to an interested audience ranging from thousands to millions. These users are news curators, and are the main subject of study of this paper. We adopt the perspective of a journalist or news editor who wants to discover news curators among the audience engaged with a news site. We look at the users who shared a news story on Twitter and attempt to identify news curators who may provide more information related to that story. In this paper we describe how to find this specific class of curators, which we refer to as news story curators. Hence, we proceed to compute a set of features for each user, and demonstrate that they can be used to automatically find relevant curators among the audience of two large news organizations.

[1]  P. Pirolli,et al.  It's Not in Their Tweets: Modeling Topical Expertise of Twitter Users , 2012, 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing.

[2]  Krishna P. Gummadi,et al.  Inferring who-is-who in the Twitter social network , 2012, WOSN '12.

[3]  Barry Smyth,et al.  Terms of a Feather: Content-Based News Recommendation and Discovery Using Twitter , 2011, ECIR.

[4]  Krishna P. Gummadi,et al.  Cognos: crowdsourcing search for topic experts in microblogs , 2012, SIGIR '12.

[5]  Timothy W. Finin,et al.  Why we twitter: understanding microblogging usage and communities , 2007, WebKDD/SNA-KDD '07.

[6]  Ling Feng,et al.  A Tweet-Centric Approach for Topic-Specific Author Ranking in Micro-Blog , 2011, ADMA.

[7]  Alex Hai Wang,et al.  Don't follow me: Spam detection in Twitter , 2010, 2010 International Conference on Security and Cryptography (SECRYPT).

[8]  Mounia Lalmas,et al.  Transient News Crowds in Social Media , 2013, ICWSM.

[9]  Qi He,et al.  TwitterRank: finding topic-sensitive influential twitterers , 2010, WSDM '10.

[10]  Timothy W. Finin,et al.  Why We Twitter: An Analysis of a Microblogging Community , 2009, WebKDD/SNA-KDD.

[11]  David Hawking,et al.  Panoptic Expert: Searching for experts not just for documents , 2001 .

[12]  Hongbo Deng,et al.  Formal Models for Expert Finding on DBLP Bibliography Data , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[13]  Elizabeth Yakel.  Digital curation , 2007, OCLC Syst. Serv..

[14]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[15]  Igor Brigadir,et al.  A system for twitter user list curation , 2012, RecSys '12.

[16]  Virgílio A. F. Almeida,et al.  Detecting Spammers on Twitter , 2010 .

[17]  Qi Gao,et al.  Interweaving Trend and User Modeling for Personalized News Recommendation , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[18]  Aristides Gionis,et al.  From chatter to headlines: harnessing the real-time web for personalized news recommendation , 2012, WSDM '12.

[19]  Wai-Tat Fu,et al.  Understanding experts' and novices' expertise judgment of twitter users , 2012, CHI.

[20]  B. Zelizer.  Journalists as interpretive communities , 1993 .

[21]  Elizabeth Yakel.  Presidential libraries: merging public records and private lives , 2007, OCLC Syst. Serv..

[22]  Scott Counts,et al.  Identifying topical authorities in microblogs , 2011, WSDM '11.

[23]  Deepak Agarwal,et al.  Multi-faceted ranking of news articles using post-read actions , 2012, CIKM '12.